Responsibilities

Lead and grow the AI/ML Engineering team, coordinating execution across data scientists on collaborative projects.
Design, deliver, and operate the core AI/ML platform: agent frameworks, evaluation harnesses, labeling systems, document processing systems, semantic search, knowledge bases, model hosting.
Run AI/ML systems at scale in production with reliability, observability, performance, and incident response.
Create processes to turn proof-of-concept code from Data Science into production-grade services.
Partner with the Chief AI Officer and Product Manager to build forward-looking product strategy.
Run stand-ups, capacity planning, and drive predictability across engineering and data science.
Provide leadership to ensure the cross-functional team can utilize AI technologies for coding, PR reviews, testing, observability, and incident response.

Requirements

BS or MS in Computer Science (or equivalent experience).
5+ years managing teams of ~8+ engineers with hands-on technical leadership.
8+ years direct hands-on technical contributor experience in backend services.
3+ years building AI/ML production-grade services at scale for multiple use cases, with direct collaboration with data science and engineering.
Strong in Java, Scala, Rust, or similar backend languages, plus Python.
Understanding of productizing ML/AI platforms — workflows, serving, observability, reliability, and scale.
Fluent in data science concepts to partner effectively with DS leadership.
Strong communicator, organized, proactive, comfortable with ambiguity.